This dissertation consists of three separate research projects. Each paper uses a different applied econometric technique to investigate problems related to air quality economics. The first chapter is a general introduction to all three studies. The second chapter explores adopting an environmentally-friendly public transportation system in Europe. The Bayesian econometric methods show that willingness to pay for a new public transportation system is primarily driven by improvements to public goods, such as air quality and greenhouse gas emission reduction. The third chapter uses the red tide-related stated experience and satellite imagery of chlorophyll-a concentration as well as field data of respiratory irritation. This chapter illustrates that ancillary scientific information can be efficiently combined with choice experimental data. The fourth chapter uses panel fixed-effect models to investigate the short-term effect of air pollution on students' cognitive performance in China. It is shown that PM2.5 has a significantly negative impact on students' exam performance. / Doctor of Philosophy / This dissertation consists of three separate research projects. The first chapter is a general introduction to all three chapters. The second chapter assesses residents' support for environmentally-friendly public transportation (EFPT) upgrades across Europe. We develop a novel Bayesian logit model to investigate residents' willingness to pay for local EFPT upgrades. We find evidence that WTP is primarily driven by expected improvements to public goods, such as air quality and greenhouse gas abatement, as opposed to private ridership benefits. WTP distributions are strongly positive in all nations suggesting implicit public support for EFPT in Europe. The third chapter presents a unique opportunity to validate stated experiences by Florida Gulf coast residents with red tide-related air toxins with satellite imagery of chlorophyll-a concentration, as well as field data on respiratory irritation at local beaches. We find that respondents are more likely to choose our proposed new harmful algal blooms forecast system when the chlorophyll-a concentration or respiratory irritation is higher at nearby coastal locations. Moreover, we illustrate that this ancillary scientific information can be efficiently combined with choice experimental data and consider this research a first step in a broader effort to directly link scientific data on environmental conditions with nonmarket economic outcomes. The fourth chapter investigates short-term exposure of air pollution on students' cognitive performance in a high-stakes exam: China's College English Test (CET). We use student fixed effects in the panel-data model to estimate the effect of air pollution on students' test scores. Our findings indicate a statistically significant negative effect of PM2.5 on exam performance and also show PM2.5 is equally harmful to listening and reading section, and maybe even more for writing section. We also find that short-term exposure causes negative cognitive effects, suggesting that temporary preventative measures could be effective in avoiding the negative effects of PM2.5.